Smoking bans are sweeping Europe. New research suggests that these bans reduce smoking amongst those directly affected and their families and peers, creating what could be called a “public health multiplier”.

European smokers are ‘out in the cold’ these days, figuratively and literally. Ireland was the first to ban smoking in all enclosed spaces (in 2004). France, Italy, Norway, Scotland, Sweden and many others have since jumped on the band wagon.1 The typical argument for these bans turns on protecting non-smokers from second-hand smoke. Recent research suggests a more important justification – smoking is contagious.

That people’s behaviours depend upon their social setting is hardly a revelation. But such effects are rarely taken into formal consideration in policy formulation since the connections have not been quantified. No longer. A large and growing empirical literature demonstrates that people’s choices are influenced by those of their friends and peers – including health-related choices. For example, a recent study suggested that the US obesity ‘epidemic’ spread from person to person like a virus.2

Is smoking subject to the same mechanism? In recent research, David Cutler and Ed Glaeser examine the role of social interactions in the decision to smoke cigarettes and found ‘Interpersonal complementaries’ to be enormously important.3

Devil in the detail: peer effects versus peer selection

To move beyond generalities, one has to think about the mechanisms.

Smoking is both an individual and social activity. If one's friends step outside for a smoke break, the personal reward from joining them rises. Similarly, if one's friends don't smoke, there is a social cost to smoking alone or asking friends to step out with you. Peer behaviour may also influence one's beliefs. Friends who light up implicitly communicate information about the benefits of smoking, and smokers may also be more likely to articulate the view that cigarettes are pleasurable or not harmful. These peer effects compete with other sources of information (the horrible pictures, stark health warnings, etc.).

But the causality could also be run the other way. You may be making friends with other smokers since they smoke. This possibility makes it tricky to empirically identify the size of peer effects.

The Cutler-Glaeser study uses a clever tactic (what economists call an identification strategy) to get at peer effects – specifically at the impact that husbands and wives have on each other’s smoking habits. Using data from the US Current Population Survey, Cutler and Glaeser find that that a person whose spouse smokes is 21% more likely to smoke themselves. But smoking in a couple is obviously affected by both peer selection (smokers are more likely to marry) and peer effects (smokers are more likely to quit if their spouse does). To sort these out, they need to find something that affects the smoking of one spouse without affecting the likelihood that the pair will get married. Workplace smoking bans – which in the US can be company-specific or building-specific – provide an almost ideal lever for prying out the selection effect. Workers subject to workplace smoking bans are 4.6% less likely to smoke but such bans are unlikely to have much impact on spousal selection.4

The authors find an astounding result. Using the smoking-ban to separate effects, they find a peer effect of 40%! Roughly speaking, this means that the spouse of a person that quits due to a smoking ban is 40% less likely to smoke than otherwise would be the case. That is a huge public health multiplier.

The very plausible idea that individuals’ smoking decisions depend upon the smoking decisions of their neighbours and peers has important implications for public policy. The most obvious is that exogenous forces that make one person’s smoking less likely – such as public space smoking bans – will decrease the probability that a peer will also smoke. Thinking more broadly, it also suggests that geographically broad bans will be more effective since more people in a particular social group will be affected. In other words, nation-wide bans will have greater multiplier effects than regional or city-wide bans.

This column first appeared (in Dutch) on our Consortium partner's site Me Judice.

Footnotes

1 See the European Public Health Alliance’s list of European smoking bans.2 Christakis, Nicholas A. and James H. Fowler, “The Spread of Obesity in a Large Social Network over 32 Years”, New England Journal of Medicine, 357(4), July 26, 2007, 370-379.3 Cutler, David M. and Edward L. Glaeser, “Social Interactions and Smoking,” NBER Working Paper 13477.4 This confirms earlier research; Evans, William N., Farrelly, Matthew C. and Montgomery, Edward B., "Do Workplace Smoking Bans Reduce Smoking?" American Economic Review, 89(5), September 1999, 729-747.